f i i iForest fragmentation in a micro watershed of Western Himalayawatershed of Western Himalaya

Amit Y., Uttam K.,Ramachandra T.V.amit503sm@gmail.com

Center for Ecological Sciences, I di I tit t f S i B lIndian Institute of Science, Bangalore.

IntroductionF t f t ti i th h b• Forest fragmentation is the process whereby a large, continuous area of forest is both reduced in

d di id d i farea and divided into two or more fragments.

The decline in the size of the forest and the increasing gisolation between the two remnant patches of the forest has been cited as one of the major cause of d li i bi di ideclining biodiversity

The fragmentation studies saw a rise in number after two of the classic theoriesof the classic theories –

A. The Island biogeographic theory (Mac Arthur and Wilson, 1963), )

EquilibriumI

EqRate

Number

B. Metapopulation dynamics (Levins, 1967)

S d i k l tiSource and sink population Extinction and re-colonization Connecti it pla s an important roleConnectivity plays an important role

• Himalaya one of the 34 biodiversity hot spot has the growth rate of 2 47% higher than thehas the growth rate of 2.47% , higher than the average growth rate of all other biodiversity hotspots(1 8%)hotspots(1.8%).

• The people of Himalaya have been dependent f h i d f i i i l hi hfor their needs from time immemorial which has lead to the fragmentation of forests of Hi lHimalaya.

• Our study area is a small watershed of Sutlej River, located near to Shimla District of Himachal Pradesh

Th t d t h d i W t Hi l ( l i )The study watershed in Western Himalaya (google image)

STUDY AREA

Himachal Pradesh

India

Moolbari watershed

Analysis1 B d1. Boundary

Done by using SOI toposheets- 53E/4/NW2 Gird making

25 ha . Grid ( 500m by 500 m were made25 ha . Grid ( 500m by 500 m were made using Map Info software. Out of total 72 grids 39 were taken forOut of total 72 grids 39 were taken for analysis.

3 Di iti i th d i t k (t h t)3. Digitizing the drainage network (toposheet)

4. Calculation of slope:Slope = BC / AB

BSlope = BC / ABIt was calculated for all the

streams in the grid and A C

gthe grid was assigned the slope of the longest t f lli ithi itstream falling within it.

5. Calculation of aspect:Th di ti f fl ( 8The direction of flow( 8 categ.) of water was assigned to each stream gand given a number from 1 to 8 starting from north in clockwise direction.

Classified image of Moolbari Watershed by Maximum Likelihood classifier

6. Image classification ( maximum likely hood classifier) :IRS P -6. image, year 2007Maximum likely hood classification 4 categoriesMaximum likely hood classification- 4 categoriesa. Agriculturalb. Forestc. Barrend. Built-up

7. Forest categoriesg(Riitters et. al).:- Computation of Pf and Pff for a 3 x 3 grid of

pixels. Forest pixels-shaded & non forest –not shadedForest pixels shaded & non forest not shaded.Pf = forest/ non forest = 6/9 = 0.67

Pff No of pixel pairs having atleast one pixel as forestPff = No. of pixel pairs having atleast one pixel as forest Total number cardinal pixel being forest

Pff= 5/11 = 0.45

InteriorUndetermined

1.0 Interior- all neighbors are forest

EdgePerforated

0.6

gPerforated- central part is a

clearing Patch patch forest on non forest

Patch

Transitional0.4

Patch- patch forest on non forest background

Edge- out side edge of a forest i i l h lf h i hb

0.0 pff0.0

1.0 Transitional – half the neighbours

are forest.Undetermined – not falling in any g y

of the above

Classification of forest into six categories as per the valuesClassification of forest into six categories as per the values of Pf and Pff

1.

Classifies image of forest class according to Riitters method

• 8. Grid wise analysis of Forest categories for the 39 grids by Ritters method (Riitters et al )g y ( )

• 9. Grid wise analysis of Fragmentation indices-

a. Total Forest area (A)b. Percentage of total land (Pland) c. Number of patches ( NP)p ( )d. Patch Density ( PD) e. Largest Patch Index (LPI) f. Mean Area of patch ( Mean area)f. Mean Area of patch ( Mean _area)g. Mean Gyrate ( mean_ gyrate)h. Mean shape Index ( Shape_ Mean)i Mean Para ( perimeter to area ratio)i. Mean_Para ( perimeter to area ratio)

For details:-http://www.umass.edu/landeco/research/fragstats/fragstats.html

Slope Vs Forest

RESULT

0.6

0.8

1

ope

y = 0.0008x + 0.353; R2 = 0.0141

0

0.2

0.4

0 20 40 60 80 100

Slo

0 20 40 60 80 100

Forest(%)

Stream density Vs forest

8

10

sity

y = -0.006x + 5.8645; R2 = 0.0116

0

2

4

6

Stre

am d

ens

00 20 40 60 80 100Forest(%)

Relation of land cover percentage onRelation of land cover percentage on the forest indices

CA Pland NP PD LPI AreaMean

GyrateMean

Shapemean

ParaMean(m-1)

Agricult -0 800 -0 809 0 449 0 428 -0 833 -0 734 -0 720 -0 506 0 758Agriculture

0.800 0.809 0.449 0.428 0.833 0.734 0.720 0.506 0.758

Barren -0.678 -0.679 -0.678 -0.679 -0.551 -0.478 0.470

Built-up -0 420 -0 423 -0 409 0 349Built-up -0.420 -0.423 -0.409 0.349

Table1. Showing significant correlation values (P<0.05) betweendifferent land use categories and fragmentation indices (Fragstats)different land use categories and fragmentation indices (Fragstats) Analysis done in “PAST” Software.

LPI Vs Land use area100 00

80.00

100.00

Agricult ure

60.00

PI

Barren

Built up

40.00

L

0.00

20.00

0.00 20.00 40.00 60.00 80.00 100.00

land use area (%)LPI A i lt B B iltLPI Agriculture Barren Built_upR2 0.795 0.4001 0.1675

CA Vs Land use area30.00

Agricultu

Barren

Built up

20.00

CA

10.00

C

0 000.000.00 20.00 40.00 60.00 80.00

CA A i lt B B iltCA Agriculture Barren BuiltupR2 0.6406 0.4593 0.1768

Para_mean Vs Land use area1600.00

1200.00

1400.00

800.00

1000.00

ra_m

ean

400.00

600.00para

AgricultureBarren

0.00

200.00

0 00 20 00 40 00 60 00 80 00 100 00

Built up

0.00 20.00 40.00 60.00 80.00 100.00

Land use area (%)

PARA_mean Agriculture Barren BuiltupR2 0.5753 0.2205 0.122

Correlation of categories of forest with the other land use type

Patch Transition Perforated InteriorAgriculture 0.366 0.502 0.301 -0.578

(P>0.05)( )

ConclusionConclusion• The topography i.e. the slope and aspect of the

land did not show any relation with the forestland did not show any relation with the forest cover of the land.

• Amongst the three land cover category it is the• Amongst the three land cover category it is the Agricultural land cover which shows maximum correlation with the forest fragmentation indices as gevident from the above analysis, indicating that the agriculture is spreading over the forested area.

References• Galicia Leopoldo, Zarco-Arista Alba Esmeralda, Ivette Mendoza-RoblesGalicia Leopoldo, Zarco Arista Alba Esmeralda, Ivette Mendoza Robles

Karla, Palacio-Prieto José Luis and García-Romero Arturo; 2008; Land use/cover, landforms and fragmentation patterns in a tropical dry forest in the southern Pacific region of Mexico, Singapore Journal of Tropical Geography, Vol 29(2) pp 137-154Vol. 29(2), pp 137 154.

• Lele N., Joshi P.K. , and Agrawal S.P. 2008. Assessing forest fragmentation in northeastern region (NER) of India using landscape matrices, Ecological indicators, 8(5), pp 657-663 M A h R b H Ed d O Wil 1967 Th Th f I l d• Mac Arthur Robert H., Edward O Wilson 1967. The Theory of Island Biogeography. Princeton university press. New Jersey

• McGarigal, K., S. A. Cushman, M. C. Neel, and E. Ene. 2002. FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps. Computer software p y g g p pprogram produced by the authors at the University of Massachusetts, Amherst. Available at the following web site: www.umass.edu/landeco/research/fragstats/fragstats.html

• Riitters K Wickham J O'Neill R Jones B and Smith E 2000 Global scaleRiitters K., Wickham J., O Neill R., Jones B. and Smith E.. 2000. Global scale patterns of forest fragmentation. Conservation Ecology 4(2), p. 3.

• Acknowledgement:Th h h kf l h D fThe authors are thankful to the Department of Science and technology for the funding the projectproject.

We also express our thanks to Dr. K V Gururaja for Image classification of the study areafor Image classification of the study area.

Thank you!